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United States Department of Agriculture

Agricultural Research Service

Title: Modeling Soil Carbon Transported by Water Erosion Processes

Authors
item Starr, G - OSU-SCHOOL OF NATURAL RES
item Lal, R - OSU-SCHOOL OF NATURAL RES
item Malone, Robert
item Hothem, Daniel
item Owens, Lloyd
item Kimble, J - USDA-NRCS

Submitted to: Land Degradation and Development
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 19, 1999
Publication Date: N/A

Interpretive Summary: Given the intense interest by both scientists and policy makers with the fate of carbon, it is important to understand the principle factors and processes involved with soil organic carbon (SOC) sequestration. One of these factors is erosion. Long term monitoring to directly assess SOC loss by erosion would be ideal but expensive, therefore, diagnostic models to assess erosional SOC have been developed. The objective of this study was to identify and describe approaches for assessing erosional impacts on SOC dynamics using models. Using 12 years of data, two modeling approaches were compared; one approach relates SOC loss to soil loss on an event basis and another approach relates SOC loss to soil loss using an enrichment ratio (ER). Enrichment implies that eroded soil has a higher organic carbon content than the near surface soil, and the ER for the watersheds used in this study was determined to be 2.1. An advantage of the ER approach is the simplicity and the ease of computing cumulative SOC loss over a long time period from cumulative soil loss. The main advantage of the first approach is it is more accurate than the ER approach but it is not easy to compute cumulative SOC loss from cumulative soil loss for numerous individual runoff events. A third modeling approach was presented that relates runoff aggregate size distribution to fate of SOC loss by soil erosion. Based upon this approach, the larger soil aggregates, a minimum of about 73% of all aggregates, are deposited on the landscape whereas the smaller aggregates, with the most stable SOC, are transported to aquatic ecosystems. This research will benefit policy makers in making decisions concerning SOC fate on a large scale, and it adds to our understanding of the erosional impacts on SOC.

Technical Abstract: Long-term monitoring is needed for direct assessment of soil organic carbon (SOC), soil, and nutrient loss by water erosion on a watershed scale. However labor and capital requirements preclude implementation of such monitoring at many locations representing principal soils and ecoregions. These considerations warrant the development of diagnostic models to assess serosional SOC loss from more readily obtained data. The same factors affec transport of SOC and mineral soil fraction, suggesting that given the gain or loss of conservative soil minerals, it may be possible to estimate the SOC flux from the data on erosion and deposition. One possible approach to parameterization is the use of the Revised Universal Soil Loss Equation (RUSLE) to predict soil loss and this multiplied by the percent of SOC in the near surface soil and an enrichment factor to obtain SOC loss. The data obtained from two watersheds in Ohio indicate that a power law relationship pbetween soil loss and SOC loss may be more appropriate. When measured SOC loss in individual events over a 12 yr period was plotted against measured soil loss the data are logarithmically linear (R**2=0.75) with a slope (or exponent in the power law) slightly less than would be expected for a RUSLE type model. The stable aggregate size distribution in runoff on a plot scale may be used to guess the fate of size pools of SOC by comparing size distributions in the runoff plot scale and river watershed scales. Based upon this comparison, a minimum of 73% of material from runoff plots is deposited on the landscape and the most stable carbon pool is lost from watershed soils to aquatic ecosystems and atmospheric carbon dioxide. Implicit in these models is the supposition that water stable soil aggregates and primary particles can be viewed as a tracer for SOC.

Last Modified: 8/1/2014
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